How to Write a Pull Request Description That Gets Approved

PRs with explicit code explanations are 12% to 20% more likely to be merged, and more than 34% of real GitHub pull requests in a large study still had empty descriptions. That's not a style issue, it's a review bottleneck you can fix with better writing.

A pull request description does more than summarize code. It gives reviewers the context they need to approve faster, spot risk sooner, and avoid guessing what changed or why. In practice, the difference between a good and bad description is often the difference between a smooth review and a thread full of back-and-forth questions.

Why Most Pull Request Descriptions Fail Today

The first problem is simple, and it shows up at scale. In a 2019 study of 333,001 PRs from 1,000 engineered Java projects on GitHub, 114,466 pull requests had empty descriptions, and more than 34% were empty overall, which means missing context wasn't a rare mistake, it was a recurring pattern in real collaboration study. When a description is blank or vague, reviewers spend their first minutes reconstructing intent instead of reviewing code.

The second problem is even more practical. In a later review of 80,000 PRs, Code Explanation appeared in 55.39% of descriptions, and PRs with that element were 12% to 20% more likely to be merged review. That doesn't mean prose alone gets code approved, but it does show that explanation is part of the mechanics of successful review.

An infographic showing that 35 percent of GitHub pull requests lack descriptions, leading to slower reviews and abandonment.

Why this matters in day-to-day review

A description is a control surface for the review process. It tells a teammate whether to check logic, edge cases, rollout risk, or just skim for a quick bug fix. Without that signal, even a strong diff can feel harder to trust.

A good description saves more reviewer time than a polished commit message ever will.

The habit also scales across distributed teams. When your reviewer isn't sitting next to you, the pull request description becomes the nearest thing to a design note, test plan, and change summary in one place.

Element	Frequency in PRs
Purpose	54.54%
Code Explanation	55.39%
Link	45.16%

For teams trying to tighten writing discipline around engineering work, the standards for concise technical clarity in technical writing best practices translate directly into better pull request descriptions. The same rule applies: if the reader has to infer the point, the writing is failing.

The Three Reviewer Questions Every Description Must Answer

A weak pull request description usually fails in the same place, it leaves reviewers guessing about the change, the reason behind it, or the exact thing they should verify. A strong description answers three questions in order. What changed comes first, why it changed comes second, and how to review or test it comes third. That order matters because reviewers do not all need the same depth, but they do need the same orientation.

GitHub's guidance points to the same structure in different words, purpose, overview, and links to supporting context such as issues or prior discussions GitHub docs. Atlassian's guidance adds a practical detail for UI work, screenshots or recordings can catch regressions that a text diff will miss. The description has to serve both code and context, and it has to do that without forcing the reviewer to reconstruct the change from the diff alone.

Bad description versus useful description

Bad:

Fixed the filter issue.

Useful:

What changed: The product filter now keeps the selected value after navigation.
Why: Users were losing state when they returned from a detail page.
How to test: Open the catalog, choose a filter, navigate to an item, then go back and confirm the filter is still applied.

The second version is short, but it gives the reviewer a path. It avoids implementation detail that does not help the first pass, and it does not force someone to chase the bug report just to understand the change.

A description like this also makes review comments more precise. Instead of “Can you explain this?”, the conversation starts at the core issue, whether that is behavior, edge cases, or the test plan.

If a reviewer cannot tell what to check in the first pass, the description is underwritten.

One more rule helps here. Put the main point first, then add the reason, then say how to verify it. That keeps the reviewer's mental model aligned with the diff from line one.

A Reusable Template You Can Paste Into Any PR

Use a structure that keeps the important parts in the same place every time. A pull request description should feel predictable to reviewers, because predictability lowers friction. The template below covers the pieces that matter most without turning into bureaucratic filler.

Copy-paste template

Summary
One sentence on what this PR does. Leave out implementation detail here.

Why
The problem, bug, or decision that made this change necessary. Don't repeat the summary.

What Changed
A short bullet list of the actual code or behavior changes. Keep it concrete.

How to Test
Clear verification steps a reviewer can run or validate in staging.

Risk & Rollout
Only include this when the change can break behavior, needs sequencing, or depends on a flag or migration.

Screenshots
Use for UI work, visual changes, or anything where a diff won't show the outcome.

Related Links
Link to the ticket, design doc, incident, or prior discussion that gave this PR context.

Filled-in example for a backend bug fix

Summary
Fix the cache key collision in the pricing service.

Why
Two different product tiers were being stored under the same key, which caused the wrong price to appear after a catalog refresh.

What Changed

Updated the key format to include tier ID.
Added a regression test for mixed-tier requests.

How to Test
Run the pricing endpoint with two tier IDs, refresh the catalog, and confirm each tier returns the correct value.

Risk & Rollout
Low risk, no schema change, no deployment order dependency.

Filled-in example for a UI change

Summary
Update the checkout button label to match the new copy.

Why
The previous label no longer matched the approved flow on mobile checkout.

What Changed

Replaced the button text in the checkout modal.
Adjusted spacing so the longer label wraps cleanly.

How to Test
Open checkout on desktop and mobile widths, confirm the label renders correctly, and verify there's no clipping.

This format stays useful when you trim it down. For a cosmetic PR, you can skip Risk & Rollout. For a trivial text change, Screenshots may be enough without a long explanation. The point isn't to force every slot into every PR, it's to make the useful context easy to find.

Documenting Risk, Rollback, and Breaking Changes

The details most descriptions skip are the ones reviewers need when a change affects production. If a PR touches migrations, feature flags, or customer-visible behavior, the description should tell the team what can go wrong and what happens if it does. That turns the description into a working agreement, not just a summary.

A useful way to write this is to make rollback and rollout explicit. A reviewer should be able to answer, in under a minute, whether the change is reversible, whether order matters, and whether a breaking change will affect downstream consumers. That kind of detail belongs in the PR itself, not buried in a separate thread.

What to spell out

Reversibility: Say whether the change can be rolled back safely, and if not, say why.
Migration order: State whether the database, app, or feature flag changes must land first.
Feature flag behavior: Note whether the new path is off by default, staged, or already live.
Breaking impact: Call out API changes, renamed fields, or behavior that could affect clients.
Operational note: Mention who should deploy first when the rollout has a dependency chain.

A guide on release notes templates is useful here because the same discipline applies. If a customer-facing change has rollout constraints, those constraints should be visible where the change is reviewed, not just where it is announced.

A common failure looks like this. A developer ships a database migration and app code in the same PR, but the description only says “updated user profile storage.” Reviewers approve it, deployment starts, and the on-call engineer discovers the app expects the new column before the migration is fully applied. The rollback path isn't clear, so recovery takes longer than it should have.

The better version is blunt and actionable.

Rollout note: Apply the migration first, then deploy the app code. Rollback is safe only after traffic drains from the new code path.

That sentence gives the reviewer a decision point. It also gives the person deploying the change a sequence they can follow without improvising under pressure.

Matching Description Depth to PR Size

A small PR doesn't need a novel, but it does need enough context to avoid guesswork. I've seen short, focused changes sail through review because the description was crisp, while larger refactors stalled because the author buried the rationale under implementation details. The pattern is consistent, small PRs win when the description is tight and specific, large PRs win when the same clarity is scaled up.

A fast approval usually looks like this

One team I worked with had a 90-line bug fix approved in about two hours. The description did four things well, it gave a one-line summary, explained the reason in a single sentence, listed a focused test plan, and attached a screenshot for the only visible change. Reviewers didn't have to ask for context, so they stayed in the code instead of chasing the author.

The larger PR from the same team told a different story. It was about 1,400 lines, and the description tried to describe every implementation choice in the same breath. The rationale was there, but it was buried, so reviewers spent two days asking for clarification on the architectural change before they could judge the diff confidently.

The lesson isn't “write more” when the PR grows. It's “write sharper.” Large changes need a clearer explanation of the shape of the work, the risks, and the testing path, not extra paragraphs that repeat the code.

Use the same four patterns at any size

One-line summary: Say what changed without naming every file.
Single-sentence rationale: Explain the bug, constraint, or product need.
Tight test plan: Show the exact path a reviewer should validate.
Visual proof when needed: Add a screenshot or recording if text alone won't show the result.

The guidance in how reviewers want pull requests written lines up with the same practical boundary, keep routine PRs small and focused when possible, and make larger or multi-component changes easier to review by decomposing them clearly. That doesn't mean every PR must stay tiny. It means larger PRs have to work harder on explanation because the diff already asks more of the reviewer.

The bigger the change, the less patient the reviewer is with vague prose.

When AI-Assisted Descriptions Help and When They Hurt

AI can draft a pull request description quickly, and that's useful when the change set is repetitive or the author is working in a second language. It can also help on big refactors where the author knows the change well but doesn't want to spend ten minutes shaping the opening summary. Used that way, it's a drafting aid.

The risk starts when the model smooths over the parts reviewers care about most. AI-written summaries can omit rollout notes, flatten tradeoffs, or invent confidence where the author hasn't checked the details. That's especially dangerous if the description is meant to guide deployment or explain a behavior change.

Human review has to stay in the loop

The practical rule set is short.

Check the rollout context: Confirm that migrations, flags, and reversibility are still stated plainly.
Verify linked issues: Make sure any issue number, ticket, or design link is real and relevant.
Add one human sentence: Say why this approach was chosen, especially if there was a tradeoff.
Scan for overconfidence: Remove language that sounds certain when the code still has limits.

The current literature around automatic PR description generation points in the same direction, useful assistance exists, but it doesn't replace the reviewer contract built around clarity and trust automatic PR description generation. That's the standard. If AI helps you get to a cleaner first draft, great. If it shortens the thinking process, it's working against the review.

For teams that want speed without losing signal, the right approach is to treat AI as a formatter of intent, not a substitute for intent. A description still needs a human to decide what matters, what carries risk, and what another engineer needs to know before approving the change.

A One-Page Checklist and Automation Hooks

A good description becomes a habit when the team can check it quickly and enforce the basics automatically. The goal is not to turn every PR into paperwork. The goal is to make missing context harder to ship than including it.

A checklist for pull request descriptions paired with automated CI and linting workflow hooks.

One-page checklist

Summary filled: Does the first line say what changed?
Why explained: Is the reason for the change obvious?
Changes listed: Are the key edits named, not just implied?
Testing steps included: Can a reviewer verify the behavior without guessing?
Screenshots attached when relevant: Would a visual help confirm the result?
Risks noted: Did you mention rollout order, reversibility, or breaking impact?
Related links added: Is the issue or discussion easy to find?
No filler: Can someone understand the PR without reading three times?

Automation that keeps the habit alive

A repository PR template is the easiest starting point, because it makes the right fields available before the author starts typing. A DESCRIPTION_REQUIRED CI check can block empty submissions, which helps prevent the blank-description problem called out earlier in the article. A lint rule that flags missing test steps catches a common failure mode before review begins.

A practical writing tool can help too. RewriteBar can be used to tighten the language of a draft pull request description before it goes live, especially when a developer wants a clearer summary or a cleaner tone. That's most useful after the author has already written the facts, not before.

The related guide on code documentation tools is worth looking at if your team wants to standardize more of this workflow. The point is to remove friction without removing judgment.

If you want proof that the habit is working, track a few signals over the next quarter, such as time to first review, empty-description rate, and merge rate. Those numbers won't tell you everything, but they'll tell you whether the team is getting faster because the description now does real work.

If your team wants pull request descriptions that are clearer before review and easier to trust during approval, try RewriteBar as part of the drafting step. It helps tighten summaries, improve clarity, and clean up the wording before the PR reaches a reviewer.